Backend engineer building distributed systems and AI-powered infrastructure.
• Designing resilient microservices and API platforms
• Event-driven and streaming architectures
• AI-integrated backend systems
• Retrieval-augmented and knowledge-driven workflows
• Production-grade Python services
Applied LLM systems · RAG architectures · Agentic backend workflows ·
Streaming systems · Container-native engineering
Python · TypeScript
FastAPI · Django · Flask
REST · GraphQL · Microservices
Next.js · React · TypeScript
PostgreSQL · BigQuery
MongoDB · Cassandra
Redis · Valkey
Chroma . Qdrant
Kafka · RabbitMQ · GCP Pub/Sub · MQTT
GCP . Docker · Kubernetes · Terraform
Git · GitHub · GitLab · Jenkins · Airflow
Prometheus · Grafana
Auth0
Jira · Confluence
• AI should augment systems, not complicate them
• Design for reliability and observability first
• Keep architecture simple, scalable, and operable
• Build backend systems that integrate intelligence, not bolt it on
